Abstract 4277: Measuring proliferation rates of distinct tumour clones using single-cell DNA sequencing
Authors: Olivia Lucas, Sophie Ward, Rija Zaidi, Mark Hill, Emilia Lim, Haoran Zhai, Abigail Bunkum, Sonya Hessey, Michelle Dietzen, Andrew Rowan, Cristina Naceur-Lombardelli, Nnenna Kanu, Mariam Jamal-Hanjani, Charles Swanton, Simone Zaccaria
Journal: Cancer Research (2023)

Abstract Background: Tumour proliferation rate is a key phenotypic feature of cancer, with higher rates linked to poorer clinical outcomes. Thus far, proliferation rates have been measured using pathological or experimental techniques on bulk tumour samples. However, while tumours are heterogeneous compositions of distinct clones with varying levels of fitness, measuring the proliferation of individual clones has not been possible to date. We hypothesise that enabling the identification of the most proliferative clones would reveal genomic hallmarks of aggressive clones, or the prediction of their potential phenotype, e.g., metastatic potential. Methods: We have developed SPRINTER (Single-cell Proliferation Rate Inference in Neoplasms Through Evolutionary Routes), a novel computational method to measure proliferation rates in individual tumour clones using single-cell whole-genome DNA sequencing. To assess the accuracy and power of SPRINTER, we have also developed an experimental approach to DNA sequence &amp;gt;18,000 single cells, accurately separated in different DNA-replication phases. We have sequenced and applied SPRINTER to &amp;gt;10,000 non-small cell lung cancer cells from longitudinal and metastatic tumour samples within the TRACERx study and PEACE autopsy programme. We have further analysed published data from &amp;gt;10,000 breast cancer cells. Results: We demonstrate that SPRINTER can accurately identify subpopulations of cells with different proliferation rates using relatively small numbers of cells, in contrast to previous preliminary approaches. While our estimates are concordant with previous bulk experimental studies (5-40%), we importantly have identified clonal heterogeneity in proliferation rates. Using bulk analysis, we have identified patterns of dissemination of tumour clones in non-small cell lung cancer. Integrating this with single-cell data, our results indicate that more widely disseminating tumour clones have higher proliferation rates, suggesting a link between proliferation and dissemination potential. We additionally find that clones are more proliferative in the metastatic versus the primary setting. Furthermore, we have identified high proliferation clones that may have a selective advantage in a breast tumour, and have inferred that they likely arose recently in cancer evolution. Conclusions: We have developed a novel method that enables accurate identification of proliferation rates of individual tumour clones using single-cell DNA sequencing data, allowing the investigation of genomic hallmarks in highly proliferative clones that might lead to higher fitness. Citation Format: Olivia Lucas, Sophie Ward, Rija Zaidi, Mark Hill, Emilia Lim, Haoran Zhai, Abigail Bunkum, Sonya Hessey, Michelle Dietzen, Andrew Rowan, Cristina Naceur-Lombardelli, Nnenna Kanu, Mariam Jamal-Hanjani, Charles Swanton, Simone Zaccaria. Measuring proliferation rates of distinct tumour clones using single-cell DNA sequencing. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4277.